Auradine

AI Research Architect

Show

You will study modern AI model architectures including transformers and emerging alternatives and analyze how their mathematical and algorithmic structure maps onto efficient hardware implementations. You will help answer questions such as which model architectures are best suited for real world AI systems such as robotics and drones, how models should evolve when compute efficiency becomes a primary constraint, and how model structures and algorithms can be modified to better align with efficient silicon implementations. This role sits at the boundary between AI research, algorithms, and hardware architecture, and offers the opportunity to influence both the models we run and the silicon that runs them.

Responsibilities

  • Analyze modern AI model architectures—including transformers and emerging alternatives—to understand their computational structure and system requirements.
  • Study the mathematical and algorithmic properties of models to identify opportunities for architectural innovation.
  • Explore modifications to model structures, training approaches, or dataflows that improve efficiency on specialized hardware.
  • Collaborate closely with hardware architects to translate model characteristics into efficient compute and memory architectures.
  • Investigate model architectures suited for real-time and embodied AI systems, including robotics and autonomous machines.
  • Develop insights into how future AI models will interact with system constraints such as latency, power, and memory bandwidth.
  • Track emerging research in machine learning and identify opportunities where new model architectures may benefit from specialized hardware.

Requirements

  • Strong background in machine learning, deep learning, or related fields.
  • Deep understanding of modern model architectures, including transformers and related approaches.
  • Strong mathematical foundation in machine learning, optimization, and deep learning algorithms.
  • Experience working with ML frameworks such as PyTorch, JAX, or TensorFlow.
  • Ability to analyze model computation and translate it into system-level implications.
  • Interest in the intersection of AI models, algorithms, and compute architecture.

Benefits

  • Medical, dental, and vision coverage
  • Paid time off
  • Flexible work arrangements
  • Professional development opportunities
  • Other benefits designed to support the well-being and growth of the team